基于机器学习的加密货币监管风险指数
A Machine Learning Based Regulatory Risk Index for Cryptocurrencies
摘要：
加密货币的价值往往对重大政策变化做出积极反应，但现有的指数都没有反映与监管变化相关的市场风险。在本文中，我们量化了金融科技和加密货币（CC）新规带来的风险，并分析了它们对市场动态的影响。具体来说，加密货币监管风险指数（CRRIX）是根据与政策相关的新闻报道频率构建的。从顶级在线CC新闻平台收集未标记的新闻数据，并使用潜在Dirichlet分配模型和Hellinger距离进一步分类。我们的研究结果表明，基于机器学习的CRRIX成功地捕捉到了重大的政策变化时刻。市场波动指数VCRIX和CRRIX的走势是同步的，这意味着CRRIX可能对加密货币市场的所有参与者都有帮助。算法和Python代码可在www.quantlet.de上进行研究。
英文摘要：
Cryptocurrencies' values often respond aggressively to major policy changes, but none of the existing indices informs on the market risks associated with regulatory changes. In this paper, we quantify the risks originating from new regulations on FinTech and cryptocurrencies (CCs), and analyse their impact on market dynamics. Specifically, a Cryptocurrency Regulatory Risk IndeX (CRRIX) is constructed based on policy-related news coverage frequency. The unlabeled news data are collected from the top online CC news platforms and further classified using a Latent Dirichlet Allocation model and Hellinger distance. Our results show that the machine-learning-based CRRIX successfully captures major policy-changing moments. The movements for both the VCRIX, a market volatility index, and the CRRIX are synchronous, meaning that the CRRIX could be helpful for all participants in the cryptocurrency market. The algorithms and Python code are available for research purposes on www.quantlet.de.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
